Compare Gemini Ultra vs. Gemini Pro

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Understand and compare Gemini Ultra vs. Gemini Pro

Generate side-by-side samples for these models in the Context.ai playground

Overview

	Gemini Ultra	Gemini Pro
Provider The entity that provides this model.	Google	Google
Input Context Window The number of tokens supported by the input context window.	32.8K characters	32.8K characters
Maximum Output Tokens The number of tokens that can be generated by the model in a single request.	8,192 characters	8,192 characters
Release Date When the model was first released.	Unknown	December 13th, 2023 7 months ago 2023-12-13

Pricing

	Gemini Ultra	Gemini Pro
Input Cost of input data provided to the model.	Pricing not available.	Pricing not available.
Output Cost of output tokens generated by the model.	Pricing not available.	Pricing not available.

Benchmarks

Compare relevant benchmarks between Gemini Ultra and Gemini Pro.

	Gemini Ultra	Gemini Pro
MMLU Evaluating LLM knowledge acquisition in zero-shot and few-shot settings.	83.7 (5-shot) Source	71.8 (5-shot) Source
MMMU A wide ranging multi-discipline and multimodal benchmark.	59.4 (0-shot pass@1) Source	47.9 (pass@1) Source
HellaSwag A challenging sentence completion benchmark.	Benchmark not available.	Benchmark not available.

Gemini Ultra, developed by Google, features a large context window of 32768 tokens. The model has excelled in benchmarks like MMMU with a score of 59.4 in a 0-shot pass@1 scenario and MMLU with a score of 83.7 in a 5-shot scenario.

Gemini Pro, developed by Google, features a context window of 32768 tokens. The model costs 0.0125 cents per thousand tokens for input and 0.0375 cents per thousand tokens for output. It was released on December 13, 2023, and has achieved a score of 47.9 in the MMMU benchmark with a "pass@1" caveat and a score of 71.8 in the MMLU benchmark in a 5-shot scenario.

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